Social media is one the fastest-growing segment. The term ‘social media’, as used herein, means a way to transmit or share information with a larger audience. One of the popular channels of social media is social networks, which are platforms to engage, interact, communicate and collaborate with users. The term ‘social network’, as used herein, means web-based services that allow members to construct a public or a semi-public profile within the boundary of that particular community. Social networks provide a facility to consolidate a list of other members with whom a member may want to share a connection.
Social media channels provide platforms to express opinions and share ideas about companies or products, which make social media of utmost importance in corporate communications, public relations and advertising campaigns. This property of Social media, and, in turn, social networks, to engage a large number of members as potential content generators yields massive source of information. Hence, businesses require solutions to monitor the social media for a member's opinion towards their brands as well as to increase their brand recognition and influence opinions. For example, current guidelines do not mandate any stringent application level security other than encryption of the transmission media. Accordingly, HTTS based interfaces between a handheld computing device and in-store server components are merely designed to ensure that card data is secure during transmission. As a result, with these new types of POS emerging, higher levels of security to protect this sensitive transaction POS data are needed.
In order to influence a member's opinion, companies look to identify the key influencers. The term ‘influencer’, as used herein, means a member who transmits information, through social media channels, that have an impact on other member's ideas and practices. Members of the social media who get the most attention may be considered as influencers for a particular topic on a social media channel. These members have the power to affect other member's opinions, and thus their perception of the brand and purchase decisions. Influence is dynamic and depends on variety of factors for example, perceived authority and audiences reach. Influential zones can be found across social media, for example, Facebook®, Twitter®, blogs and forums by applying social network analysis technics.
There exist several methodologies for identifying influencers. Trusov, Bodapati et al describe how to identify influencers, given member's behavior among his network of friends. The approach proposes a non-standard form of Bayesian shrinkage implemented in a Poisson regression. Instead of shrinking across panelists, strength is pooled across variables within the model for each member. The approach identifies the specific members who most influence others' activity. Cha, Haddadi, Benevenuto, Gummad et al describe how to measure member influence in Twitter® by comparing three measures: 1) indegree influence, the number of followers of a member, directly indicates the size of the audience for that user 2) retweet influence, measured through the number of retweets containing one's name, indicates the ability of that member to generate content, 3) mention influence, measured through the number of mentions containing one's name, indicates the ability of that member to engage others in a conversation. This approach examines how the influential members perform in spreading popular news topics by investigating the dynamics of an individual's influence by topic and over time and characterizing the precise behaviors that make ordinary individuals gain high influence over a short period of time. Wu, Hofman, Mason, Watts et al describe a method for analysis of ‘lists’ feature of Twitter® to distinguish between elite members and ordinary members to different news topics. This solution examines attention on Twitter® paid by the different member categories to different news topics. Bakshy, Hofman, Mason, Watts et al describe investigation of the attributes and relative influence of Twitter® members by tracking diffusion events. This approach tries to identify influencers by: 1) determining members who have been influential in the past and who have a large number of followers, 2) finding web-links that were rated interesting. Weng, Lim, Jiang, He et al describe analyzing impact of member's followers and persons that member follows. TwitterRank, an extension of PageRank is used to identify influencers taking the link structure and topical similarity between members into consideration. The underlying assumption of this approach is homophily between members, which mean that twitterers follow other members because of the topical similarity between them and their friends. Agarwal, Liu, Tang, Yu et al describe a method for determining influential bloggers based on analyzing bloggers properties: recognition i.e. number of in-links, activity generation i.e. number of comments, novelty i.e. number of out-links and eloquence i.e. length of post. Moon, Han et al describe a quantitative method for identifying influential bloggers by weighting readers based on homophily and vulnerability with bloggers. This approach is based on the Quantifying Influence Model (QIM), which includes two components: 1) interpersonal similarity, which presents the interaction among bloggers and interpersonal similarity between readers 2) degree of information propagation, which represents how many readers a blogger has, where the readers diffuse the blog posts.
The above-mentioned methodologies describe different methods of analyzing social media channels, particularly, conversations in social networks. For the purposes of this disclosure, the social media channel, particularly, social network conversations are referred to as ‘Conversari Platform’. These methods focus on social networks and do not take into account other social media channels, for example, but not limited to, product launches, product evangelizations, conference presentations, content platforms, product recommendations and research papers. This may lead to inaccurate identification of influencers and their estimated influence. For the purposes of this disclosure, this category of social media channels is referred to as ‘Published Platform’.
There lies a need to ascertain scores of influencers by taking into account the ‘Published Platform in addition to the ‘Conversari Platform’. The present disclosure improves the accuracy of identifying influencers and quantifying their influence by taking into account the ‘Published Platform’.